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Principal Manifolds for Data Visualization and Dimension Reduction - Lecture Notes in Computational Science and Engineering Alexander N Gorban 2008 edition
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Principal Manifolds for Data Visualization and Dimension Reduction - Lecture Notes in Computational Science and Engineering
Alexander N Gorban
The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering algorithms, principal manifolds and SOM. New approaches to NLPCA, principal manifolds, branching principal components and topology preserving mappings are described.
364 pages, 68 black & white illustrations, 14 colour illustrations, 22 black & white tables, biograp
| メディア | 書籍 Paperback Book (ソフトカバーで背表紙を接着した本) |
| リリース済み | 2007年10月1日 |
| ISBN13 | 9783540737490 |
| 出版社 | Springer-Verlag Berlin and Heidelberg Gm |
| ページ数 | 340 |
| 寸法 | 155 × 235 × 13 mm · 517 g |
| 言語 | ドイツ語 |
| 編集者 | Gorban, Alexander N. |
| 編集者 | Kegl, Balazs |
| 編集者 | Wunsch, Donald C. |
| 編集者 | Zinovyev, Andrei |
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